import torch
import torch.nn as nn
import numpy as np

num_time_steps = 50
input_size=1
hidden_size=16
output_size=1
lr=0.01


rnn = nn.RNN(1, 16)

start = np.random.randint(3)
time_steps = np.linspace(start, start + 10, num_time_steps)
data = np.sin(time_steps)
# data = data.reshape(num_time_steps, 1) # 
x = torch.tensor(data[:-1].reshape(1, num_time_steps -1, 1)).float()
y = torch.tensor(data[1:].reshape(1, num_time_steps -1, 1)).float()



rnn(x)